123 citations · 305 across the 26 of their papers we have counts for
7 papers · 1 filter
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna
Wing and Tip decomposition construct a hierarchy of butterfly-dense edge and vertex induced bipartite subgraphs, respectively. They have applications in several domains including e…
A High Throughput Parallel Hash Table on FPGA using XOR-based Memory
Ruizhi Zhang, Sasindu Wijeratne, Yang Yang +2
Hash table is a fundamental data structure for quick search and retrieval of data. It is a key component in complex graph analytics and AI/ML applications. State-of-the-art paralle…
DYNAMAP: Dynamic Algorithm Mapping Framework for Low Latency CNN Inference
Yuan Meng, Sanmukh Kuppannagari, Rajgopal Kannan +1
Most of the existing work on FPGA acceleration of Convolutional Neural Network (CNN) focus on employing a single strategy (algorithm, dataflow, etc.) across all the layers. Such an…
RECEIPT: REfine CoarsE-grained IndePendent Tasks for Parallel Tip decomposition of Bipartite Graphs
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna +1
Tip decomposition is a crucial kernel for mining dense subgraphs in bipartite networks, with applications in spam detection, analysis of affiliation networks etc. It creates a hier…
GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms
Hanqing Zeng, Viktor Prasanna
Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art deep learning model for representation learning on graphs. It is challenging to accelerate training of GCNs…
Planting Trees for scalable and efficient Canonical Hub Labeling
Kartik Lakhotia, Qing Dong, Rajgopal Kannan +1
Point-to-Point Shortest Distance (PPSD) query is a crucial primitive in graph database applications. Hub labeling algorithms compute a labeling that converts a PPSD query into a li…